A team of bioengineers at the Indian Institute of Technology (IIT) Bombay has created BrainProt and DrugProtAI, innovative platforms to consolidate data on various brain diseases. BrainProt v3.0, a comprehensive database, integrates diverse biological information to offer insights into brain function in healthy and diseased conditions. This system merges data from genomics, transcriptomics, proteomics, and biomarker research into a single portal, facilitating research on human brain diseases.
Prof. Sanjeeva Srivastava from the Department of Biosciences and Bioengineering at IIT Bombay mentioned that BrainProt includes resources to analyze protein expression variations between the left and right hemispheres of the human brain across 20 neuroanatomical regions. It is the first resource of its kind, encompassing data on 56 human brain diseases and 52 multi-omics datasets from over 1,800 patient samples. These datasets cover transcriptomic and proteomic data for several diseases, enabling users to explore disease-associated genes and proteins, their validation, and activity levels in patient samples.
The development of DrugProtAI aims to assess the druggability of proteins before conducting extensive experiments. Currently, only a small percentage of human proteins have FDA-approved drugs, emphasizing the need for efficient target selection. Dr. Ankit Halder, a study co-author, explained that DrugProtAI predicts a protein’s druggability by considering factors beyond its sequence, such as cellular location and structural attributes. It generates a “druggability index” indicating the likelihood of a protein being druggable, streamlining the identification of potential drug targets.
Integrating DrugProtAI into BrainProt creates a seamless process for researchers to transition from identifying disease markers to evaluating druggability and exploring existing compounds or clinical trials swiftly. This integration enhances the efficiency of research processes, offering a comprehensive platform for brain disease research within a short timeframe.
